Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots

Yong Liu; Jiajun Sun; Yanqing Lin; Virpi Kristiina Tuunainen

doi:10.1007/978-3-031-94184-9_5

Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots

Yong Liu^*, Jiajun Sun, Yanqing Lin, Virpi Kristiina Tuunainen

^*Corresponding author for this work

Information Systems Science, Helsinki

Aalto University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

Numerous studies have explored human preferences for male versus female robots, producing inconsistent findings and varied explanations for the manifestation of gender bias towards robots. This study contributes to understanding how user gender and robot gender interact to influence users’ evaluations of robots by analyzing over 1100 survey responses on 23 robots, distinguished by their male and female appearances. The findings refute the existence of the same-gender or cross-gender effect. Specifically, we found a general preference for female robots over male robots. In addition, female users report the highest likeability scores for female robots compared to other human-robot gender combinations.

Original language	English
Title of host publication	E-Business. Generative Artificial Intelligence and Management Transformation - 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings
Editors	Yiliu Paul Tu, Maomao Chi
Number of pages	10
Publisher	Springer
Publication date	08.06.2025
Pages	52-61
ISBN (Print)	978-3-031-94183-2
ISBN (Electronic)	978-3-031-94184-9
DOIs	https://doi.org/10.1007/978-3-031-94184-9_5
Publication status	Published - 08.06.2025
MoE publication type	A4 Article in conference proceedings
Event	24th Wuhan International Conference on E-Business, WHICEB 2025 - Guangzhou, China Duration: 06.06.2025 → 08.06.2025

Publication series

Name	Lecture Notes in Business Information Processing
Volume	549 LNBIP
ISSN (Print)	1865-1348
ISSN (Electronic)	1865-1356

Keywords

512 Business and Management
Adoption
Bias
Gender
Gender-Match
Human-Robot-Interaction

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10.1007/978-3-031-94184-9_5

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Liu, Y., Sun, J., Lin, Y., & Tuunainen, V. K. (2025). Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. In Y. P. Tu, & M. Chi (Eds.), E-Business. Generative Artificial Intelligence and Management Transformation - 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings (pp. 52-61). (Lecture Notes in Business Information Processing; Vol. 549 LNBIP). Springer. https://doi.org/10.1007/978-3-031-94184-9_5

Liu, Yong ; Sun, Jiajun ; Lin, Yanqing et al. / Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. E-Business. Generative Artificial Intelligence and Management Transformation - 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings. editor / Yiliu Paul Tu ; Maomao Chi. Springer, 2025. pp. 52-61 (Lecture Notes in Business Information Processing).

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title = "Exploring the Impacts of Human-Robot Gender Match on Users{\textquoteright} Perceptions of Robots",

abstract = "Numerous studies have explored human preferences for male versus female robots, producing inconsistent findings and varied explanations for the manifestation of gender bias towards robots. This study contributes to understanding how user gender and robot gender interact to influence users{\textquoteright} evaluations of robots by analyzing over 1100 survey responses on 23 robots, distinguished by their male and female appearances. The findings refute the existence of the same-gender or cross-gender effect. Specifically, we found a general preference for female robots over male robots. In addition, female users report the highest likeability scores for female robots compared to other human-robot gender combinations.",

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Liu, Y, Sun, J, Lin, Y & Tuunainen, VK 2025, Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. in YP Tu & M Chi (eds), E-Business. Generative Artificial Intelligence and Management Transformation - 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings. Lecture Notes in Business Information Processing, vol. 549 LNBIP, Springer, pp. 52-61, 24th Wuhan International Conference on E-Business, WHICEB 2025, Guangzhou, China, 06.06.2025. https://doi.org/10.1007/978-3-031-94184-9_5

Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. / Liu, Yong; Sun, Jiajun; Lin, Yanqing et al.
E-Business. Generative Artificial Intelligence and Management Transformation - 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings. ed. / Yiliu Paul Tu; Maomao Chi. Springer, 2025. p. 52-61 (Lecture Notes in Business Information Processing; Vol. 549 LNBIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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T1 - Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots

AU - Liu, Yong

AU - Sun, Jiajun

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AU - Tuunainen, Virpi Kristiina

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025/6/8

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AB - Numerous studies have explored human preferences for male versus female robots, producing inconsistent findings and varied explanations for the manifestation of gender bias towards robots. This study contributes to understanding how user gender and robot gender interact to influence users’ evaluations of robots by analyzing over 1100 survey responses on 23 robots, distinguished by their male and female appearances. The findings refute the existence of the same-gender or cross-gender effect. Specifically, we found a general preference for female robots over male robots. In addition, female users report the highest likeability scores for female robots compared to other human-robot gender combinations.

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Liu Y, Sun J, Lin Y, Tuunainen VK. Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots. In Tu YP, Chi M, editors, E-Business. Generative Artificial Intelligence and Management Transformation - 24th Wuhan International Conference on E-business, WHICEB 2025, Proceedings. Springer. 2025. p. 52-61. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-031-94184-9_5

Exploring the Impacts of Human-Robot Gender Match on Users’ Perceptions of Robots

Abstract

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Keywords

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